Reducing Invisible Losses with Shrinkage Detection

Solution Shrinkage Detection
Solution Shrinkage Detection
Industry CPG
Region US
Technology Microsoft Azure
Context
CPG companies increasingly struggle with inventory shrinkage as complex supply chains and limited retailer data create visibility gaps. These blind spots lead to revenue leakage, distorted demand signals, and inefficient production and replenishment decisions. Shrinkage also skews performance metrics, resulting in misaligned commercial strategies and higher operational costs. By integrating fragmented data and detecting anomalies in real time, AI-driven shrinkage detection restores transparency, reduces losses, improves forecast accuracy, and strengthens decision-making across the value chain. 
Problem Statement

The client faced complex challenges that underscored the need for intelligent shrinkage detection. Limited data visibility from retailers restricted their ability to validate inventory losses. Shrinkage was often hidden within business noise created by merchandising resets, planogram changes, availability gaps, pricing shifts, and fluctuating demand. Additionally, static shrink thresholds failed to adjust for seasonality, demand patterns, or local events, making anomalies harder to isolate and act upon at scale. 

Impact

  • Reduced baseline shrink rate by ~9% 
  • $16M revenue opportunity unlocked within 12 months 
  • Achieved an organization-wide adoption rate of 85% 
  • Adjusted operating margins by ~20% 

 

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